This paper discusses and documents the algorithms of SsfPack 2.2. SsfPack is a suite of C routines for carrying out computations involving the statistical analysis of univariate and multivariate models in state space form. The emphasis is on documenting the link we have made to the Ox computing...

Realized kernels use high-frequency data to estimate daily volatility of individual stock prices. They can be applied to either trade or quote data. Here we provide the details of how we suggest implementing them in practice. We compare the estimates based on trade and quote data for the same...

This paper is concerned with the Bayesian estimation of non-linear stochastic differential equations when only discrete observations are available. The estimation is carried out using a tuned MCMC method, in particular a blcked Metropolis-Hastings algorithm, by introducing auxiliary points and...

This paper derives the exact distribution of the maximum likelihood estimator of a first-order linear autoregression with an exponential disturbance term. We also show that, even if the process is stationary, the estimator is T-consistent, where T is the sample size. In the unit root case, the...

In this paper we will rigourously study some of the properties of continuous time stochastic volatility models. We have five main results, including: the stochastic volatility class can be linked to Cox process based models of tick-by-tick financial data; we characterise the moments,...